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1.
Application of snowmelt runoff model for water resource management   总被引：1，自引：0，他引：1  
Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R2) and volume difference (DV) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R2 is 0·87 and average volume difference DV is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

2.
Snow is one of the most active natural elements of snow cover through its high albedo, variation of the the cryosphere on the earth surface. Its unique proper- snow cover distribution and frozen soils in regional ties, such as areal extent, surface albedo, and snow scales not only affect local climate and environments, depth are important parameters in global energy bal- but also feedback to large-scale, or even global cli- ance models. On global and terrestrial scales, a large matic change th…  相似文献   

3.
The snow treatment becomes an important component of Soil and Water Assessment Tool (SWAT)’s hydrology when spring flows are dominated by snow melting. However, little is known about SWAT's snow hydrology performance because most studies using SWAT were conducted in rainfall‐driven catchments. To fill this gap, the present study aims to evaluate the ability of SWAT in simulating snow‐melting‐dominated streamflow in the Outardes Basin in Northern Quebec. SWAT performance in simulating snowmelt is evaluated against observed streamflow data and compared to simulations from the operationally used Streamflow Synthesis and Reservoir Regulation (SSARR) model over that catchment. The SWAT 5‐year calibration showed a satisfactory performance at the daily and seasonal time scales with low volume biases. The SWAT validation was conducted over two (17‐year and 15‐year) periods. Performances were similar to the calibration period in simulating the daily and seasonal streamflows again with low model biases. The spring‐snowmelt‐generated peak flow was accurately simulated by SWAT both in magnitude and timing. When SWAT's results are compared to SSARR, similar performances in simulating the daily discharges were observed. SSARR simulates more accurately streamflow generated at the snowmelt onset whereas SWAT better predicts streamflow in summer, fall and winter. SWAT provided reasonable streamflow simulations for our snow‐covered catchment, but refinement of the process‐driven baseflow during the snowmelt onset could improve spring performances. Therefore, SWAT becomes an attractive tool for evaluating water resources management in Nordic environments when a distributed model is preferred or when water quality information (e.g. temperature) is required. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

4.
An accurate simulation of snowmelt runoff is of much importance in arid alpine regions. Data availability is usually an obstacle to use energy‐based snowmelt models for the snowmelt runoff simulation, and temperature‐based snowmelt models are more appealing in these regions. The snow runoff model is very popular nowadays, especially in the data sparse regions, because only temperature, precipitation and snow cover data are required for inputs to the model. However, this model uses average temperature as index, which cannot reflect the snowmelt simulation in the high altitude band. In this study, the snow runoff model is modified on the basis of accumulated active temperature. Snow cover calculation algorithm is added and is no longer needed as input but output. This makes the model able to simulate long‐time runoff and long‐time snow cover variation in every band. An examination of the improved model in the Manas River basin showed that the model is effective. It can reproduce the behaviour of the hydrology and can reflect the actual snow cover fluctuation. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

5.
Remote sensing is an important source of snow‐cover extent for input into the Snowmelt Runoff Model (SRM) and other snowmelt models. Since February 2000, daily global snow‐cover maps have been produced from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS). The usefulness of this snow‐cover product for streamflow prediction is assessed by comparing SRM simulated streamflow using the MODIS snow‐cover product with streamflow simulated using snow maps from the National Operational Hydrologic Remote Sensing Center (NOHRSC). Simulations were conducted for two tributary watersheds of the Upper Rio Grande basin during the 2001 snowmelt season using representative SRM parameter values. Snow depletion curves developed from MODIS and NOHRSC snow maps were generally comparable in both watersheds: satisfactory streamflow simulations were obtained using both snow‐cover products in larger watershed (volume difference: MODIS, 2·6%; NOHRSC, 14·0%) and less satisfactory streamflow simulations in smaller watershed (volume difference: MODIS, −33·1%; NOHRSC, −18·6%). The snow water equivalent (SWE) on 1 April in the third zone of each basin was computed using the modified depletion curve produced by the SRM and was compared with in situ SWE measured at Snowpack Telemetry sites located in the third zone of each basin. The SRM‐calculated SWEs using both snow products agree with the measured SWEs in both watersheds. Based on these results, the MODIS snow‐cover product appears to be of sufficient quality for streamflow prediction using the SRM in the snowmelt‐dominated basins. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

6.
Daily swath MODIS Terra Collection 6 fractional snow cover (MOD10_L2) estimates were validated with two‐day Landsat TM/ETM + snow‐covered area estimates across central Idaho and southwestern Montana, USA. Snow cover maps during spring snowmelt for 2000, 2001, 2002, 2003, 2005, 2007, and 2009 were compared between MODIS Terra and Landsat TM/ETM + using least‐squared regression. Strong spatial and temporal map agreement was found between MODIS Terra fractional snow cover and Landsat TM/ETM + snow‐covered area, although map disagreement was observed for two validation dates. High‐altitude cirrus cloud contamination during low snow conditions as well as late season transient snowfall resulted in map disagreement. MODIS Terra's spatial resolution limits retrieval of thin‐patchy snow cover, especially during partially cloudy conditions. Landsat's image acquisition frequency can introduce difficulty when discriminating between transient and resident mountain snow cover. Furthermore, transient snowfall later in the snowmelt season, which is a stochastic accumulation event that does not usually persist beyond the daily timescale, will skew decadal snow‐covered area variability if bi‐monthly climate data record development is the objective. As a quality control step, ground‐based daily snow telemetry snow‐water‐equivalent measurements can be used to verify transient snowfall events. Users of daily MODIS Terra fractional snow products should be aware that local solar illumination and sensor viewing geometry might influence fractional snow cover estimation in mountainous terrain. Cross‐sensor interoperability has been confirmed between MODIS Terra and Landsat TM/ETM + when mapping snow from the visible/infrared spectrum. This relationship is strong and supports operational multi‐sensor snow cover mapping, specifically climate data record development to expand cryosphere, climate, and hydrological science applications. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

7.
The spatio‐temporal distribution of snow in a catchment during ablation reflects changes in the total amount of snow water equivalent and is thus a key parameter for the estimation of melt water run‐off. This study explores possible rules behind the spatial variability of snow depth during the ablation season in a small Alpine catchment with complex topography. The snow depth observations are based on more than 160 000 terrestrial laser scanner data points with a spatial resolution of 1 m, which were obtained from 11 scanning campaigns of two consecutive ablation seasons. The analysis suggests that for estimating cumulative snow melt dynamics from the catchment investigated, assessing the initial snow distribution prior to the melt season is more important than addressing spatial differences in the melt behaviour. Snow volume and snow‐covered area could be predicted well using a conceptual melt model assuming spatially uniform melt rates. However, accurate results were only obtained if the model was initialized with a pre‐melt snow distribution that reflected measured mean and standard deviation. Using stratified melt rates on the other hand did not improve the model results. At least for sites with similar meteorological and topographical conditions, the model approach presented here comprises an efficient way to estimate snow depletion dynamics, especially if persistent snow accumulation pattern between years facilitate the characterization of the initial snow distribution prior to the melt. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

8.
A degree‐day‐based model is presented for a 1 year ahead runoff forecast, with 1 day time steps. The input information is a single snowpack evaluation collected at the beginning of the snowmelt season. The snow‐cover dynamics, the key information for long‐term snowmelt forecast, are described by the snow‐line dynamics, i.e. by the movements of the downhill snowpack limit. The snowmelt volume, estimated by the snow‐line dynamics, is the exogenous input of an autoregressive transformation model. The model is calibrated by a least‐squares procedure on the basis of observed daily runoff data and the corresponding measurements of the snowpack volume (one measurement per year). A real‐world case study on the Alto Tunuyan River basin (2380 km2, Argentinean Andes) is presented. The 1 year ahead Alto Tunuyan River runoff patterns, computed for both calibration and validation periods, reveal high agreement with observed streamflows. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

9.
To improve simulations of regional‐scale snow processes and related cold‐season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth‐generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land‐surface model. One important cause for the underestimated SWE in Noah is its unrealistic land‐surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow‐season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near‐surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over‐predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5–CLM3 due to the lower evaporation resulting from the longer snow duration. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

10.
Snow cover depletion curves are required for several water management applications of snow hydrology and are often difficult to obtain automatically using optical remote sensing data owing to both frequent cloud cover and temporary snow cover. This study develops a methodology to produce accurate snow cover depletion curves automatically using high temporal resolution optical remote sensing data (e.g. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua MODIS or National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR)) by snow cover change trajectory analysis. The method consists of four major steps. The first is to reclassify both cloud‐obscured land and snow into more distinct subclasses and to determine their snow cover status (seasonal snow cover or not) based on the snow cover change trajectories over the whole snowmelt season. The second step is to derive rules based on the analysis of snow cover change trajectories. These rules are subsequently used to determine for a given date, the snow cover status of a pixel based on snow cover maps from the beginning of the snowmelt season to that given date. The third step is to apply a decision‐tree‐like processing flow based on these rules to determine the snow cover status of a pixel for a given date and to create daily seasonal snow cover maps. The final step is to produce snow cover depletion curves using these maps. A case study using this method based on Terra MODIS snow cover map products (MOD10A1) was conducted in the lower and middle reaches of the Kaidu River Watershed (19 000 km2) in the Chinese Tien Shan, Xinjiang Uygur Autonomous Region, China. High resolution remote sensing data (charge coupled device (CCD) camera data with 19·5 m resolution of the China and Brazil Environmental and Resources Satellite (CBERS) data (19·5 m resolution), and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data with 15 m resolution of the Terra) were used to validate the results. The study shows that the seasonal snow cover classification was consistent with that determined using a high spatial resolution dataset, with an accuracy of 87–91%. The snow cover depletion curves clearly reflected the impact of the variation of temperature and the appearance of temporary snow cover on seasonal snow cover. The findings from this case study suggest that the approach is successful in generating accurate snow cover depletion curves automatically under conditions of frequent cloud cover and temporary snow cover using high temporal resolution optical remote sensing data. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

11.
Rain‐on‐snow events have generated major floods around the world, particularly in coastal, mountainous regions. Most previous studies focused on a limited number of major rain‐on‐snow events or were based primarily on model results, largely due to a lack of long‐term records from lysimeters or other instrumentation for quantifying event water balances. In this analysis, we used records from five automated snow pillow sites in south coastal British Columbia, Canada, to reconstruct event water balances for 286 rain‐on‐snow events over a 10‐year period. For large rain‐on‐snow events (event rainfall >40 mm), snowmelt enhanced the production of water available for run‐off (WAR) by approximately 25% over rainfall alone. For smaller events, a range of antecedent and meteorological factors influenced WAR generation, particularly the antecedent liquid water content of the snowpack. Most large events were associated with atmospheric rivers. Rainfall dominated WAR generation during autumn and winter events, whereas snowmelt dominated during spring and summer events. In the majority of events, the sensible heat of rain contributed less than 10% of the total energy consumed by snowmelt. This analysis illustrated the importance of understanding the amount of rainfall occurring at high elevations during rain‐on‐snow events in mountainous regions.  相似文献   

12.
Snow water equivalent was measured during three springs on north‐ and south‐exposed sites representing a range of stand structure and development stages of Quebec's balsam fir forest. Maximum snow water equivalent of the season, mean seasonal snowmelt rate, snowmelt season duration and total snowmelt season degree‐day factor were related to canopy height, canopy density, light interception fraction and basal area of the stands using random coefficient models. Seasonal mean snowmelt rate was better explained by stand characteristics (R2 from 0·41 to 0·61) than was maximum snow water equivalent (R2 from 0·08 to 0·23). The best relationship was found with light interception, which explained 61% of snowmelt rate variability between stands. These relationships were not significantly affected by stand aspect (Pr ≥ S = 0·14 or higher), as snow dynamics seemed less dependent on aspect than on stand characteristics. Snowmelt recovery rates could be used by forest planners to establish an acceptable time step for the harvesting of different parts of a watershed in order to prevent peak flow augmentations. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

13.
Information on regional snow water equivalent (SWE) is required for the management of water generated from snowmelt. Modeling of SWE in the mountainous regions of eastern Turkey, one of the major headwaters of Euphrates–Tigris basin, has significant importance in forecasting snowmelt discharge, especially for optimum water usage. An assimilation process to produce daily SWE maps is developed based on Helsinki University of Technology (HUT) model and AMSR‐E passive microwave data. The characteristics of the HUT emission model are analyzed in depth and discussed with respect to the extinction coefficient function. A new extinction coefficient function for the HUT model is proposed to suit models for snow over mountainous areas. Performance of the modified model is checked against the original, other modified cases and ground truth data covering the 2003–2007 winter periods. A new approach to calculate grain size and density is integrated inside the developed data assimilation process. An extensive validation was successfully performed by means of snow data measured at ground stations during the 2008–2010 winter periods. The root mean square error of the data set for snow depth and SWE between January and March of the 2008–2010 periods compared with the respective AMSR‐E footprints indicated that errors for estimated snow depth and predicted SWE values were 16.92 cm and 40.91 mm, respectively, for the 3‐year period. Validation results were less satisfactory for SWE less than 75.0 mm and greater than 150.0 mm. An underestimation for SWE greater than 150 mm could not be resolved owing to the microwave signal saturation that is observed for dense snowpack. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

14.
As large, high‐severity forest fires increase and snowpacks become more vulnerable to climate change across the western USA, it is important to understand post‐fire disturbance impacts on snow hydrology. Here, we examine, quantify, parameterize, model, and assess the post‐fire radiative forcing effects on snow to improve hydrologic modelling of snow‐dominated watersheds having experienced severe forest fires. Following a 2011 high‐severity forest fire in the Oregon Cascades, we measured snow albedo, monitored snow, and micrometeorological conditions, sampled snow surface debris, and modelled snowpack energy and mass balance in adjacent burned forest (BF) and unburned forest sites. For three winters following the fire, charred debris in the BF reduced snow albedo, accelerated snow albedo decay, and increased snowmelt rates thereby advancing the date of snow disappearance compared with the unburned forest. We demonstrate a new parameterization of post‐fire snow albedo as a function of days‐since‐snowfall and net snowpack energy balance using an empirically based exponential decay function. Incorporating our new post‐fire snow albedo decay parameterization in a spatially distributed energy and mass balance snow model, we show significantly improved predictions of snow cover duration and spatial variability of snow water equivalent across the BF, particularly during the late snowmelt period. Field measurements, snow model results, and remote sensing data demonstrate that charred forests increase the radiative forcing to snow and advance the timing of snow disappearance for several years following fire. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

15.
Ground‐penetrating radar (GPR) has become a promising technique in the field of snow hydrological research. It is commonly used to measure snow depth, density, and water equivalent over large distances or along gridded snow courses. Having built and tested a mobile lightweight set‐up, we demonstrate that GPR is capable of accurately measuring snow ablation rates in complex alpine terrain. Our set‐up was optimized for efficient measurements and consisted of a multioffset radar with four pairs of antennas mounted to a plastic sled, which was small enough to permit safe and convenient operations. Repeated measurements at intervals of 2 to 7 days were taken during the 2014/2015 winter season along 10 profiles of 50 to 200 m length within two valleys located in the eastern Swiss Alps. Resulting GPR‐based data of snow depth, density, and water equivalent, as well as their respective change over time, were in good agreement with concurrent manual measurements, in particular if accurate alignment between repeated overpasses could be achieved. Corresponding root‐mean‐square error (RMSE) values amounted to 4.2 cm for snow depth, 17 mm for snow water equivalent, and 22 kg/m3 for snow density, with similar RMSE values for corresponding differential data. With this performance, the presented radar set‐up has the potential to provide exciting new and extensive datasets to validate snowmelt models or to complement lidar‐based snow surveys.  相似文献   

16.
Because of the importance of snow for river discharge in mountain regions, hydrological research often focuses on seasonally snow-covered zones. However, in many basins the majority of the land surface area is intermittently snow-covered. Discharge monitoring in these areas is less common, so their contributions to downstream rivers remain largely unknown. We evaluated hydrological differences between three intermittently snow-covered (mean annual Jan 1–Jul 3 snow persistence <60%) and two seasonally snow-covered headwater catchments in the Colorado Front Range. We compared water balance variables to evaluate how and why discharge differs between the snow zones and estimated the relative contributions from each snow zone to regional river discharge. We focused on water years 2016–2019 and used a combination of in situ sensors and regional climate datasets. Annual discharge from the intermittent snow zone was low for all three catchments (10–77 mm), despite covering a wide range in annual snow persistence (25%–64%), whereas annual discharge from the seasonal snow zone was up to 73 times higher. Soil moisture in the seasonal snow zone was above field capacity for longer periods of time than in the intermittent snow zone, and the intermittent snow zone was uniquely subject to soil freezing (up to 102 days per year). For most of the year, potential evapotranspiration exceeded rainfall and snowmelt inputs in the intermittent snow zone, but was lower than rainfall and snowmelt inputs in the seasonal snow zone. This is likely a primary driver of the differences in soil moisture and discharge for catchments with a seasonal versus intermittent snow cover. Despite the large difference in discharge between these two snow zones, the intermittent snow zone contributed about a quarter of the discharge in the regional river, highlighting the importance of studying discharge generation across all elevations.  相似文献   

17.
Preferential subsurface flow paths known as water tracks are often the principal hydrological pathways of headwater catchments in permafrost areas, exerting an influence on slope physical and biogeochemical processes. In polar deserts, where water resources depend on snow redistribution, water tracks are mostly found in hydrologically active areas downslope from snowdrifts. Here, we measured the flow through seeping water track networks and at the front of a perennial snowdrift, at Ward Hunt Island in the Canadian High Arctic. We also used stable isotope analysis to determine the origin of this water, which ultimately discharges into Ward Hunt Lake. These measurements of water track hydrology indicated a glacio‐nival run‐off regime, with flow production mechanisms that included saturation overland flow (return flow) in a low sloping area, throughflow or pipe‐like flow in most seepage locations, and infiltration excess overland flow at the front of the snowdrift. Each mechanism delivered varying proportions of snowmelt and ground water, and isotopic compositions evolved during the melting season. Unaltered snowmelt water contributed to >90% of total flow from water track networks early in the season, and these values fell to <5% towards the end of the melting season. In contrast, infiltration excess overland flow from snowdrift consisted of a steady percentage of snowmelt water in July (mean of 69%) and August (71%). The water seeping at locations where no snow was left in August 2015 was isotopically enriched, indicating a contribution of the upper, ice‐rich layer of permafrost to late summer discharge during warmer years. Air temperature was the main driver of snowmelt, but the effect of slope aspect on solar radiation best explained the diurnal discharge variation at all sites. The water tracks in this polar desert are part of a patterned ground network, which increases connectivity between the principal water sources (snowdrifts) and the bottom of the slope. This would reduce soil–water interactions and solute release, thereby favouring the low nutrient status of the lake.  相似文献   

18.
Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.  相似文献   

19.
Snowmelt water is an important freshwater resource in the Altay Mountains in north‐west China; however, warming climate and rapid spring snowmelt can cause floods that endanger both public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature index model based on remote sensing coupled with high‐resolution meteorological data obtained from National Centers for Environmental Prediction (NCEP) reanalysis fields that were downscaled using the Weather Research Forecasting model and then bias corrected using a statistical downscaled model. Validation of the forcing data revealed that the high‐resolution meteorological fields derived from the downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of the temperature index model based on remote sensing were calibrated for spring 2014, and model performance was validated using Moderate Resolution Imaging Spectroradiometer snow cover and snow observations from spring 2012. The results show that the temperature index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash–Sutcliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt run‐off was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt run‐off accounts for 72% of spring run‐off and 21% of annual run‐off. Snowmelt is the main source of run‐off for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt run‐off predictions, so as to prevent snowmelt‐induced floods, and also provide a generalizable approach that can be applied to other remote locations where high‐density, long‐term observational data are lacking. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

20.
Modelling nutrient transport during snowmelt in cold regions remains a major scientific challenge. A key limitation of existing nutrient models for application in cold regions is the inadequate representation of snowmelt, including hydrological and biogeochemical processes. This brief period can account for more than 80% of the total annual surface runoff in the Canadian Prairies and Northern Canada and processes such as atmospheric deposition, overwinter redistribution of snow, ion exclusion from snow crystals, frozen soils, and snow‐covered area depletion during melt influence the distribution and release of snow and soil nutrients, thus affecting the timing and magnitude of snowmelt runoff nutrient concentrations. Research in cold regions suggests that nitrate (NO3) runoff at the field‐scale can be divided into 5 phases during snowmelt. In the first phase, water and ions originating from ion‐rich snow layers travel and diffuse through the snowpack. This process causes ion concentrations in runoff to gradually increase. The second phase occurs when this snow ion meltwater front has reached the bottom of the snowpack and forms runoff to the edge‐of‐the‐field. During the third and fourth phases, the main source of NO3 transitions from the snowpack to the soil. Finally, the fifth and last phase occurs when the snow has completely melted, and the thawing soil becomes the main source of NO3 to the stream. In this research, a process‐based model was developed to simulate hourly export based on this 5‐phase approach. Results from an application in the Red River Basin of southern Manitoba, Canada, shows that the model can adequately capture the dynamics and rapid changes of NO3 concentrations during this period at relevant temporal resolutions. This is a significant achievement to advance the current nutrient modelling paradigm in cold climates, which is generally limited to satisfactory results at monthly or annual resolutions. The approach can inform catchment‐scale nutrient models to improve simulation of this critical snowmelt period.  相似文献   

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